{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# FSRS4Anki Optimizer Baseline 3.26.1\n",
    "\n",
    "[![open in colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/open-spaced-repetition/fsrs4anki/blob/main/archive/candidate/baseline-3.26.1.ipynb)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Here are some settings that you need to replace before running this optimizer.\n",
    "\n",
    "filename = \"../collection-2022-09-18@13-21-58.colpkg\"\n",
    "# If you upload deck file, replace it with your deck filename. E.g., ALL__Learning.apkg\n",
    "# If you upload collection file, replace it with your colpgk filename. E.g., collection-2022-09-18@13-21-58.colpkg\n",
    "\n",
    "# Replace it with your timezone. I'm in China, so I use Asia/Shanghai.\n",
    "# You can find your timezone here: https://gist.github.com/heyalexej/8bf688fd67d7199be4a1682b3eec7568\n",
    "timezone = 'Asia/Shanghai'\n",
    "\n",
    "# Replace it with your Anki's setting in Preferences -> Scheduling.\n",
    "next_day_starts_at = 4\n",
    "\n",
    "# Replace it if you don't want the optimizer to use the review logs before a specific date.\n",
    "revlog_start_date = \"2006-10-05\"\n",
    "\n",
    "# Set it to True if you don't want the optimizer to use the review logs from suspended cards.\n",
    "filter_out_suspended_cards = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import zipfile\n",
    "import sqlite3\n",
    "import time\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import os\n",
    "import math\n",
    "from typing import List, Optional\n",
    "from datetime import timedelta, datetime\n",
    "import statsmodels.api as sm\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.ticker as ticker\n",
    "import torch\n",
    "from torch import nn\n",
    "from torch import Tensor\n",
    "from torch.utils.data import Dataset, DataLoader, Sampler\n",
    "from torch.nn.utils.rnn import pad_sequence, pack_padded_sequence, pad_packed_sequence\n",
    "from sklearn.model_selection import StratifiedGroupKFold\n",
    "from sklearn.metrics import mean_squared_error, r2_score\n",
    "from itertools import accumulate\n",
    "from tqdm.auto import tqdm\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
    "tqdm.pandas()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Deck file extracted successfully!\n",
      "revlog.csv saved.\n",
      "Trainset saved.\n",
      "Retention calculated.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0a1eddc4ceef437381dbd9f239924315",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/26286 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Stability calculated.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7c026a67d71344008bf998d51dcafad9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "analysis:   0%|          | 0/489 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Analysis saved!\n",
      "1:again, 2:hard, 3:good, 4:easy\n",
      "      r_history  avg_interval  avg_retention  stability  factor  group_cnt\n",
      "              1           1.1          0.892        1.0     inf       2063\n",
      "            1,3           3.1          0.920        4.0    4.00       1600\n",
      "          1,3,3           7.1          0.910        7.9    1.98       1320\n",
      "        1,3,3,3          16.6          0.862       10.8    1.37        986\n",
      "      1,3,3,3,3          36.5          0.840       22.3    2.06        659\n",
      "    1,3,3,3,3,3          77.0          0.861       36.4    1.63        358\n",
      "  1,3,3,3,3,3,3         117.9          0.906       38.5    1.06        177\n",
      "              2           1.0          0.902        1.1     inf        240\n",
      "            2,3           3.5          0.946        8.2    7.45        201\n",
      "          2,3,3          11.4          0.890        7.6    0.93        162\n",
      "              3           1.1          0.977        5.0     inf       4669\n",
      "            3,3           3.3          0.967       12.0    2.40       4211\n",
      "          3,3,3           8.1          0.960       19.9    1.66       3757\n",
      "        3,3,3,3          18.3          0.941       41.5    2.09       2834\n",
      "      3,3,3,3,3          35.2          0.930       50.5    1.22       1761\n",
      "    3,3,3,3,3,3          64.9          0.929       97.9    1.94       1102\n",
      "  3,3,3,3,3,3,3         100.9          0.949      143.0    1.46        530\n",
      "3,3,3,3,3,3,3,3         133.6          0.990     1821.9   12.74        131\n",
      "              4           2.0          0.976       10.7     inf       2789\n",
      "            4,3           3.7          0.976       20.4    1.91       2293\n",
      "          4,3,3           8.3          0.967       32.5    1.59       2051\n",
      "        4,3,3,3          19.8          0.958       54.5    1.68       1700\n",
      "      4,3,3,3,3          41.0          0.958       99.5    1.83       1148\n",
      "    4,3,3,3,3,3          68.1          0.956      116.1    1.17        521\n",
      "  4,3,3,3,3,3,3          78.5          0.979      110.7    0.95        248\n",
      "4,3,3,3,3,3,3,3         114.1          0.984      177.8    1.61        166\n"
     ]
    }
   ],
   "source": [
    "\"\"\"Step 1\"\"\"\n",
    "# Extract the collection file or deck file to get the .anki21 database.\n",
    "with zipfile.ZipFile(f'{filename}', 'r') as zip_ref:\n",
    "    zip_ref.extractall('./')\n",
    "    print(\"Deck file extracted successfully!\")\n",
    "\n",
    "\"\"\"Step 2\"\"\"\n",
    "if os.path.isfile(\"collection.anki21b\"):\n",
    "    os.remove(\"collection.anki21b\")\n",
    "    raise Exception(\n",
    "        \"Please export the file with `support older Anki versions` if you use the latest version of Anki.\")\n",
    "elif os.path.isfile(\"collection.anki21\"):\n",
    "    con = sqlite3.connect(\"collection.anki21\")\n",
    "elif os.path.isfile(\"collection.anki2\"):\n",
    "    con = sqlite3.connect(\"collection.anki2\")\n",
    "else:\n",
    "    raise Exception(\"Collection not exist!\")\n",
    "cur = con.cursor()\n",
    "res = cur.execute(f\"\"\"\n",
    "SELECT *\n",
    "FROM revlog\n",
    "WHERE cid IN (\n",
    "    SELECT id\n",
    "    FROM cards\n",
    "    {\"WHERE queue != -1\" if filter_out_suspended_cards else \"\"}\n",
    ")\n",
    "\"\"\"\n",
    ")\n",
    "revlog = res.fetchall()\n",
    "if len(revlog) == 0:\n",
    "    raise Exception(\"No review log found!\")\n",
    "df = pd.DataFrame(revlog)\n",
    "df.columns = ['id', 'cid', 'usn', 'r', 'ivl', 'last_lvl', 'factor', 'time', 'type']\n",
    "df = df[(df['cid'] <= time.time() * 1000) &\n",
    "        (df['id'] <= time.time() * 1000)].copy()\n",
    "\n",
    "df_set_due_date = df[(df['type'] == 4) & (df['ivl'] > 0)]\n",
    "df.drop(df_set_due_date.index, inplace=True)\n",
    "\n",
    "df['create_date'] = pd.to_datetime(df['cid'] // 1000, unit='s')\n",
    "df['create_date'] = df['create_date'].dt.tz_localize('UTC').dt.tz_convert(timezone)\n",
    "df['review_date'] = pd.to_datetime(df['id'] // 1000, unit='s')\n",
    "df['review_date'] = df['review_date'].dt.tz_localize('UTC').dt.tz_convert(timezone)\n",
    "df.drop(df[df['review_date'].dt.year < 2006].index, inplace=True)\n",
    "df.sort_values(by=['cid', 'id'], inplace=True, ignore_index=True)\n",
    "\n",
    "df['is_learn_start'] = (df['type'] == 0) & (df['type'].shift() != 0)\n",
    "df['sequence_group'] = df['is_learn_start'].cumsum()\n",
    "last_learn_start = df[df['is_learn_start']].groupby('cid')['sequence_group'].last()\n",
    "df['last_learn_start'] = df['cid'].map(last_learn_start).fillna(0).astype(int)\n",
    "df['mask'] = df['last_learn_start'] <= df['sequence_group']\n",
    "df = df[df['mask'] == True].copy()\n",
    "df.drop(columns=['is_learn_start', 'sequence_group', 'last_learn_start', 'mask'], inplace=True)\n",
    "df = df[(df['type'] != 4)].copy()\n",
    "\n",
    "type_sequence = np.array(df['type'])\n",
    "time_sequence = np.array(df['time'])\n",
    "df.to_csv(\"revlog.csv\", index=False)\n",
    "print(\"revlog.csv saved.\")\n",
    "\n",
    "df = df[(df['type'] != 3) | (df['factor'] != 0)].copy()\n",
    "df['real_days'] = df['review_date'] - timedelta(hours=int(next_day_starts_at))\n",
    "df['real_days'] = pd.DatetimeIndex(df['real_days'].dt.floor('D', ambiguous='infer', nonexistent='shift_forward')).to_julian_date()\n",
    "df.drop_duplicates(['cid', 'real_days'], keep='first', inplace=True)\n",
    "df['delta_t'] = df.real_days.diff()\n",
    "df.dropna(inplace=True)\n",
    "df['i'] = df.groupby('cid').cumcount() + 1\n",
    "df.loc[df['i'] == 1, 'delta_t'] = 0\n",
    "df = df.groupby('cid').filter(lambda group: group['type'].iloc[0] == 0)\n",
    "df['prev_type'] = df.groupby('cid')['type'].shift(1).fillna(0).astype(int)\n",
    "df['helper'] = ((df['type'] == 0) & ((df['prev_type'] == 1) | (df['prev_type'] == 2)) & (df['i'] > 1)).astype(int)\n",
    "df['helper'] = df.groupby('cid')['helper'].cumsum()\n",
    "df = df[df['helper'] == 0]\n",
    "del df['prev_type']\n",
    "del df['helper']\n",
    "\n",
    "def cum_concat(x):\n",
    "    return list(accumulate(x))\n",
    "\n",
    "t_history = df.groupby('cid', group_keys=False)['delta_t'].apply(lambda x: cum_concat([[int(i)] for i in x]))\n",
    "df['t_history']=[','.join(map(str, item[:-1])) for sublist in t_history for item in sublist]\n",
    "r_history = df.groupby('cid', group_keys=False)['r'].apply(lambda x: cum_concat([[i] for i in x]))\n",
    "df['r_history']=[','.join(map(str, item[:-1])) for sublist in r_history for item in sublist]\n",
    "df = df.groupby('cid').filter(lambda group: group['id'].min() > time.mktime(datetime.strptime(revlog_start_date, \"%Y-%m-%d\").timetuple()) * 1000)\n",
    "df['y'] = df['r'].map(lambda x: {1: 0, 2: 1, 3: 1, 4: 1}[x])\n",
    "df.to_csv('revlog_history.tsv', sep=\"\\t\", index=False)\n",
    "print(\"Trainset saved.\")\n",
    "\n",
    "df['retention'] = df.groupby(by=['r_history', 'delta_t'], group_keys=False)['y'].transform('mean')\n",
    "df['total_cnt'] = df.groupby(by=['r_history', 'delta_t'], group_keys=False)['id'].transform('count')\n",
    "print(\"Retention calculated.\")\n",
    "\n",
    "df = df.drop(columns=['id', 'cid', 'usn', 'ivl', 'last_lvl', 'factor', 'time', 'type', 'create_date', 'review_date', 'real_days', 'r', 't_history', 'y'])\n",
    "df.drop_duplicates(inplace=True)\n",
    "df['retention'] = df['retention'].map(lambda x: max(min(0.99, x), 0.01))\n",
    "\n",
    "def cal_stability(group: pd.DataFrame) -> pd.DataFrame:\n",
    "    group_cnt = sum(group['total_cnt'])\n",
    "    if group_cnt < 10:\n",
    "        return pd.DataFrame()\n",
    "    group['group_cnt'] = group_cnt\n",
    "    if group['i'].values[0] > 1:\n",
    "        r_ivl_cnt = sum(group['delta_t'] * group['retention'].map(np.log) * pow(group['total_cnt'], 2))\n",
    "        ivl_ivl_cnt = sum(group['delta_t'].map(lambda x: x ** 2) * pow(group['total_cnt'], 2))\n",
    "        group['stability'] = round(np.log(0.9) / (r_ivl_cnt / ivl_ivl_cnt), 1)\n",
    "    else:\n",
    "        group['stability'] = 0.0\n",
    "    group['avg_retention'] = round(sum(group['retention'] * pow(group['total_cnt'], 2)) / sum(pow(group['total_cnt'], 2)), 3)\n",
    "    group['avg_interval'] = round(sum(group['delta_t'] * pow(group['total_cnt'], 2)) / sum(pow(group['total_cnt'], 2)), 1)\n",
    "    del group['total_cnt']\n",
    "    del group['retention']\n",
    "    del group['delta_t']\n",
    "    return group\n",
    "\n",
    "df = df.groupby(by=['r_history'], group_keys=False).progress_apply(cal_stability)\n",
    "print(\"Stability calculated.\")\n",
    "df.reset_index(drop = True, inplace = True)\n",
    "df.drop_duplicates(inplace=True)\n",
    "df.sort_values(by=['r_history'], inplace=True, ignore_index=True)\n",
    "\n",
    "if df.shape[0] > 0:\n",
    "    for idx in tqdm(df.index, desc=\"analysis\"):\n",
    "        item = df.loc[idx]\n",
    "        index = df[(df['i'] == item['i'] + 1) & (df['r_history'].str.startswith(item['r_history']))].index\n",
    "        df.loc[index, 'last_stability'] = item['stability']\n",
    "    df['factor'] = round(df['stability'] / df['last_stability'], 2)\n",
    "    df = df[(df['i'] >= 2) & (df['group_cnt'] >= 100)].copy()\n",
    "    df['last_recall'] = df['r_history'].map(lambda x: x[-1])\n",
    "    df = df[df.groupby(['i', 'r_history'], group_keys=False)['group_cnt'].transform(max) == df['group_cnt']]\n",
    "    df.to_csv('./stability_for_analysis.tsv', sep='\\t', index=None)\n",
    "    print(\"Analysis saved!\")\n",
    "    caption = \"1:again, 2:hard, 3:good, 4:easy\\n\"\n",
    "    analysis = df[df['r_history'].str.contains(r'^[1-4][^124]*$', regex=True)][['r_history', 'avg_interval', 'avg_retention', 'stability', 'factor', 'group_cnt']].to_string(index=False)\n",
    "    print(caption + analysis)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "init_w = [1, 1, 5, -0.5, -0.5, 0.2, 1.4, -0.2, 0.8, 2, -0.2, 0.2, 1]\n",
    "\n",
    "class FSRS(nn.Module):\n",
    "    def __init__(self, w: List[float]):\n",
    "        super(FSRS, self).__init__()\n",
    "        self.w = nn.Parameter(torch.tensor(w, dtype=torch.float32))\n",
    "\n",
    "    def stability_after_success(self, state: Tensor, new_d: Tensor, r: Tensor) -> Tensor:\n",
    "        new_s = state[:,0] * (1 + torch.exp(self.w[6]) *\n",
    "                        (11 - new_d) *\n",
    "                        torch.pow(state[:,0], self.w[7]) *\n",
    "                        (torch.exp((1 - r) * self.w[8]) - 1))\n",
    "        return new_s\n",
    "\n",
    "    def stability_after_failure(self, state: Tensor, new_d: Tensor, r: Tensor) -> Tensor:\n",
    "        new_s = self.w[9] * torch.pow(new_d, self.w[10]) * torch.pow(\n",
    "            state[:,0], self.w[11]) * torch.exp((1 - r) * self.w[12])\n",
    "        return new_s\n",
    "\n",
    "    def step(self, X: Tensor, state: Tensor) -> Tensor:\n",
    "        '''\n",
    "        :param X: shape[batch_size, 2], X[:,0] is elapsed time, X[:,1] is rating\n",
    "        :param state: shape[batch_size, 2], state[:,0] is stability, state[:,1] is difficulty\n",
    "        :return state:\n",
    "        '''\n",
    "        if torch.equal(state, torch.zeros_like(state)):\n",
    "            # first learn, init memory states\n",
    "            new_s = self.w[0] + self.w[1] * (X[:,1] - 1)\n",
    "            new_d = self.w[2] + self.w[3] * (X[:,1] - 3)\n",
    "            new_d = new_d.clamp(1, 10)\n",
    "        else:\n",
    "            r = torch.exp(np.log(0.9) * X[:,0] / state[:,0])\n",
    "            new_d = state[:,1] + self.w[4] * (X[:,1] - 3)\n",
    "            new_d = self.mean_reversion(self.w[2], new_d)\n",
    "            new_d = new_d.clamp(1, 10)\n",
    "            condition = X[:,1] > 1\n",
    "            new_s = torch.where(condition, self.stability_after_success(state, new_d, r), self.stability_after_failure(state, new_d, r))\n",
    "        new_s = new_s.clamp(0.1, 36500)\n",
    "        return torch.stack([new_s, new_d], dim=1)\n",
    "\n",
    "    def forward(self, inputs: Tensor, state: Optional[Tensor]=None) -> Tensor:\n",
    "        '''\n",
    "        :param inputs: shape[seq_len, batch_size, 2]\n",
    "        '''\n",
    "        if state is None:\n",
    "            state = torch.zeros((inputs.shape[1], 2))\n",
    "        outputs = []\n",
    "        for X in inputs:\n",
    "            state = self.step(X, state)\n",
    "            outputs.append(state)\n",
    "        return torch.stack(outputs), state\n",
    "\n",
    "    def mean_reversion(self, init: Tensor, current: Tensor) -> Tensor:\n",
    "        return self.w[5] * init + (1-self.w[5]) * current\n",
    "\n",
    "class WeightClipper:\n",
    "    def __init__(self, frequency: int=1):\n",
    "        self.frequency = frequency\n",
    "\n",
    "    def __call__(self, module):\n",
    "        if hasattr(module, 'w'):\n",
    "            w = module.w.data\n",
    "            w[0] = w[0].clamp(0.1, 10)\n",
    "            w[1] = w[1].clamp(0.1, 5)\n",
    "            w[2] = w[2].clamp(1, 10)\n",
    "            w[3] = w[3].clamp(-5, -0.1)\n",
    "            w[4] = w[4].clamp(-5, -0.1)\n",
    "            w[5] = w[5].clamp(0.05, 0.5)\n",
    "            w[6] = w[6].clamp(0, 2)\n",
    "            w[7] = w[7].clamp(-0.8, -0.15)\n",
    "            w[8] = w[8].clamp(0.01, 1.5)\n",
    "            w[9] = w[9].clamp(0.5, 5)\n",
    "            w[10] = w[10].clamp(-2, -0.01)\n",
    "            w[11] = w[11].clamp(0.01, 0.9)\n",
    "            w[12] = w[12].clamp(0.01, 2)\n",
    "            module.w.data = w\n",
    "\n",
    "def lineToTensor(line: str) -> Tensor:\n",
    "    ivl = line[0].split(',')\n",
    "    response = line[1].split(',')\n",
    "    tensor = torch.zeros(len(response), 2)\n",
    "    for li, response in enumerate(response):\n",
    "        tensor[li][0] = int(ivl[li])\n",
    "        tensor[li][1] = int(response)\n",
    "    return tensor\n",
    "\n",
    "class RevlogDataset(Dataset):\n",
    "    def __init__(self, dataframe: pd.DataFrame):\n",
    "        if dataframe.empty:\n",
    "            raise ValueError('Training data is inadequate.')\n",
    "        padded = pad_sequence(dataframe['tensor'].to_list(), batch_first=True, padding_value=0)\n",
    "        self.x_train = padded.int()\n",
    "        self.t_train = torch.tensor(dataframe['delta_t'].values, dtype=torch.int)\n",
    "        self.y_train = torch.tensor(dataframe['y'].values, dtype=torch.float)\n",
    "        self.seq_len = torch.tensor(dataframe['tensor'].map(len).values, dtype=torch.long)\n",
    "\n",
    "    def __getitem__(self, idx):\n",
    "        return self.x_train[idx], self.t_train[idx], self.y_train[idx], self.seq_len[idx]\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.y_train)\n",
    "\n",
    "class RevlogSampler(Sampler[List[int]]):\n",
    "    def __init__(self, data_source: RevlogDataset, batch_size: int):\n",
    "        self.data_source = data_source\n",
    "        self.batch_size = batch_size\n",
    "        lengths = np.array(data_source.seq_len)\n",
    "        indices = np.argsort(lengths)\n",
    "        full_batches, remainder = divmod(indices.size, self.batch_size)\n",
    "        if full_batches > 0:\n",
    "            if remainder == 0:\n",
    "                self.batch_indices = np.split(indices, full_batches)\n",
    "            else:\n",
    "                self.batch_indices = np.split(indices[:-remainder], full_batches)\n",
    "        else:\n",
    "            self.batch_indices = []\n",
    "        if remainder > 0:\n",
    "            self.batch_indices.append(indices[-remainder:])\n",
    "        self.batch_nums = len(self.batch_indices)\n",
    "        # seed = int(torch.empty((), dtype=torch.int64).random_().item())\n",
    "        seed = 2023\n",
    "        self.generator = torch.Generator()\n",
    "        self.generator.manual_seed(seed)\n",
    "\n",
    "    def __iter__(self):\n",
    "        yield from (self.batch_indices[idx] for idx in torch.randperm(self.batch_nums, generator=self.generator).tolist())\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.data_source)\n",
    "\n",
    "\n",
    "def collate_fn(batch):\n",
    "    sequences, delta_ts, labels, seq_lens = zip(*batch)\n",
    "    sequences_packed = pack_padded_sequence(torch.stack(sequences, dim=1), lengths=torch.stack(seq_lens), batch_first=False, enforce_sorted=False)\n",
    "    sequences_padded, length = pad_packed_sequence(sequences_packed, batch_first=False)\n",
    "    sequences_padded = torch.as_tensor(sequences_padded)\n",
    "    seq_lens = torch.as_tensor(length)\n",
    "    delta_ts = torch.as_tensor(delta_ts)\n",
    "    labels = torch.as_tensor(labels)\n",
    "    return sequences_padded, delta_ts, labels, seq_lens\n",
    "\n",
    "class Trainer:\n",
    "    def __init__(self, train_set: pd.DataFrame, test_set: pd.DataFrame, init_w: List[float], n_epoch: int=1, lr: float=1e-2, batch_size: int=256) -> None:\n",
    "        self.model = FSRS(init_w)\n",
    "        self.optimizer = torch.optim.Adam(self.model.parameters(), lr=lr)\n",
    "        self.clipper = WeightClipper()\n",
    "        self.batch_size = batch_size\n",
    "        self.build_dataset(train_set, test_set)\n",
    "        self.n_epoch = n_epoch\n",
    "        self.batch_nums = self.next_train_data_loader.batch_sampler.batch_nums\n",
    "        self.scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(self.optimizer, T_max=self.batch_nums * n_epoch)\n",
    "        self.avg_train_losses = []\n",
    "        self.avg_eval_losses = []\n",
    "        self.loss_fn = nn.BCELoss(reduction='sum')\n",
    "\n",
    "    def build_dataset(self, train_set: pd.DataFrame, test_set: pd.DataFrame):\n",
    "        pre_train_set = train_set[train_set['i'] == 2]\n",
    "        self.pre_train_set = RevlogDataset(pre_train_set)\n",
    "        sampler = RevlogSampler(self.pre_train_set, batch_size=self.batch_size)\n",
    "        self.pre_train_data_loader = DataLoader(self.pre_train_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "\n",
    "        next_train_set = train_set[train_set['i'] > 2]\n",
    "        self.next_train_set = RevlogDataset(next_train_set)\n",
    "        sampler = RevlogSampler(self.next_train_set, batch_size=self.batch_size)\n",
    "        self.next_train_data_loader = DataLoader(self.next_train_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "\n",
    "        self.train_set = RevlogDataset(train_set)\n",
    "        sampler = RevlogSampler(self.train_set, batch_size=self.batch_size)\n",
    "        self.train_data_loader = DataLoader(self.train_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "\n",
    "        self.test_set = RevlogDataset(test_set)\n",
    "        sampler = RevlogSampler(self.test_set, batch_size=self.batch_size)\n",
    "        self.test_data_loader = DataLoader(self.test_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "        print(\"dataset built\")\n",
    "\n",
    "    def train(self, verbose: bool=True):\n",
    "        # pretrain\n",
    "        best_loss = np.inf\n",
    "        weighted_loss, w = self.eval()\n",
    "        if weighted_loss < best_loss:\n",
    "            best_loss = weighted_loss\n",
    "            best_w = w\n",
    "\n",
    "        pbar = tqdm(desc=\"pre-train\", colour=\"red\", total=len(self.pre_train_data_loader) * self.n_epoch)\n",
    "        for k in range(self.n_epoch):\n",
    "            for i, batch in enumerate(self.pre_train_data_loader):\n",
    "                self.model.train()\n",
    "                self.optimizer.zero_grad()\n",
    "                sequences, delta_ts, labels, seq_lens = batch\n",
    "                real_batch_size = seq_lens.shape[0]\n",
    "                outputs, _ = self.model(sequences)\n",
    "                stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "                retentions = torch.exp(np.log(0.9) * delta_ts / stabilities)\n",
    "                loss = self.loss_fn(retentions, labels)\n",
    "                loss.backward()\n",
    "                self.optimizer.step()\n",
    "                self.model.apply(self.clipper)\n",
    "                pbar.update(n=real_batch_size)\n",
    "\n",
    "        pbar.close()\n",
    "        for name, param in self.model.named_parameters():\n",
    "            tqdm.write(f\"{name}: {list(map(lambda x: round(float(x), 4),param))}\")\n",
    "\n",
    "        epoch_len = len(self.next_train_data_loader)\n",
    "        pbar = tqdm(desc=\"train\", colour=\"red\", total=epoch_len*self.n_epoch)\n",
    "        print_len = max(self.batch_nums*self.n_epoch // 10, 1)\n",
    "        for k in range(self.n_epoch):\n",
    "            weighted_loss, w = self.eval()\n",
    "            if weighted_loss < best_loss:\n",
    "                best_loss = weighted_loss\n",
    "                best_w = w\n",
    "\n",
    "            for i, batch in enumerate(self.next_train_data_loader):\n",
    "                self.model.train()\n",
    "                self.optimizer.zero_grad()\n",
    "                sequences, delta_ts, labels, seq_lens = batch\n",
    "                real_batch_size = seq_lens.shape[0]\n",
    "                outputs, _ = self.model(sequences)\n",
    "                stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "                retentions = torch.exp(np.log(0.9) * delta_ts / stabilities)\n",
    "                loss = self.loss_fn(retentions, labels)\n",
    "                loss.backward()\n",
    "                for param in self.model.parameters():\n",
    "                    param.grad[:2] = torch.zeros(2)\n",
    "                self.optimizer.step()\n",
    "                self.scheduler.step()\n",
    "                self.model.apply(self.clipper)\n",
    "                pbar.update(real_batch_size)\n",
    "\n",
    "                if verbose and (k * self.batch_nums + i + 1) % print_len == 0:\n",
    "                    tqdm.write(f\"iteration: {k * epoch_len + (i + 1) * self.batch_size}\")\n",
    "                    for name, param in self.model.named_parameters():\n",
    "                        tqdm.write(f\"{name}: {list(map(lambda x: round(float(x), 4),param))}\")\n",
    "        pbar.close()\n",
    "\n",
    "        weighted_loss, w = self.eval()\n",
    "        if weighted_loss < best_loss:\n",
    "            best_loss = weighted_loss\n",
    "            best_w = w\n",
    "\n",
    "        return best_w\n",
    "\n",
    "    def eval(self):\n",
    "        self.model.eval()\n",
    "        with torch.no_grad():\n",
    "            sequences, delta_ts, labels, seq_lens = self.train_set.x_train, self.train_set.t_train, self.train_set.y_train, self.train_set.seq_len\n",
    "            real_batch_size = seq_lens.shape[0]\n",
    "            outputs, _ = self.model(sequences.transpose(0, 1))\n",
    "            stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "            retentions = torch.exp(np.log(0.9) * delta_ts / stabilities)\n",
    "            tran_loss = self.loss_fn(retentions, labels)/len(self.train_set)\n",
    "            self.avg_train_losses.append(tran_loss)\n",
    "            tqdm.write(f\"Loss in trainset: {tran_loss:.4f}\")\n",
    "\n",
    "            sequences, delta_ts, labels, seq_lens = self.test_set.x_train, self.test_set.t_train, self.test_set.y_train, self.test_set.seq_len\n",
    "            real_batch_size = seq_lens.shape[0]\n",
    "            outputs, _ = self.model(sequences.transpose(0, 1))\n",
    "            stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "            retentions = torch.exp(np.log(0.9) * delta_ts / stabilities)\n",
    "            test_loss = self.loss_fn(retentions, labels)/len(self.test_set)\n",
    "            self.avg_eval_losses.append(test_loss)\n",
    "            tqdm.write(f\"Loss in testset: {test_loss:.4f}\")\n",
    "\n",
    "            w = list(map(lambda x: round(float(x), 4), dict(self.model.named_parameters())['w'].data))\n",
    "\n",
    "            weighted_loss = (tran_loss * len(self.train_set) + test_loss * len(self.test_set)) / (len(self.train_set) + len(self.test_set))\n",
    "\n",
    "            return weighted_loss, w\n",
    "\n",
    "    def plot(self):\n",
    "        fig = plt.figure()\n",
    "        ax = fig.gca()\n",
    "        ax.plot(self.avg_train_losses, label='train')\n",
    "        ax.plot(self.avg_eval_losses, label='test')\n",
    "        ax.set_xlabel('epoch')\n",
    "        ax.set_ylabel('loss')\n",
    "        ax.legend()\n",
    "        return fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6d665efec77a42ec851653a16d53358a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/88151 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tensorized!\n",
      "TRAIN: 57372 TEST: 30779\n",
      "dataset built\n",
      "Loss in trainset: 0.3341\n",
      "Loss in testset: 0.3123\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "fcfdd403c41c44b28f6b7cc3ca63ad0d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "pre-train:   0%|          | 0/15276 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "w: [1.2588, 1.8518, 5.0, -0.5, -0.5, 0.2, 1.4, -0.2, 0.8, 2.0, -0.2, 0.2, 1.0]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d980c773f0d745beaf720ef6f9b51d06",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "train:   0%|          | 0/156840 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loss in trainset: 0.3316\n",
      "Loss in testset: 0.3101\n",
      "iteration: 15360\n",
      "w: [1.2327, 2.0554, 5.2401, -1.3366, -1.1639, 0.05, 1.476, -0.15, 0.8888, 2.0642, -0.1568, 0.3447, 0.9199]\n",
      "iteration: 30720\n",
      "w: [1.2313, 2.0664, 5.3091, -1.8228, -1.4371, 0.05, 1.5368, -0.15, 0.9386, 2.0735, -0.172, 0.2893, 0.9297]\n",
      "iteration: 46080\n",
      "w: [1.2312, 2.067, 5.1756, -1.82, -1.5521, 0.05, 1.5302, -0.1804, 0.9387, 2.0758, -0.1855, 0.3562, 0.8933]\n",
      "Loss in trainset: 0.3172\n",
      "Loss in testset: 0.2975\n",
      "iteration: 60984\n",
      "w: [1.2312, 2.067, 5.1799, -1.9405, -1.6541, 0.05, 1.4829, -0.2316, 0.8883, 2.0124, -0.258, 0.3398, 0.8535]\n",
      "iteration: 76344\n",
      "w: [1.2312, 2.067, 4.9925, -1.8656, -1.6414, 0.05, 1.5321, -0.1741, 0.9293, 2.0305, -0.243, 0.2744, 0.8373]\n",
      "iteration: 91704\n",
      "w: [1.2312, 2.067, 5.0722, -2.0053, -1.7443, 0.05, 1.4873, -0.2288, 0.8849, 2.0728, -0.2052, 0.3092, 0.767]\n",
      "Loss in trainset: 0.3169\n",
      "Loss in testset: 0.2971\n",
      "iteration: 106608\n",
      "w: [1.2312, 2.067, 4.987, -1.9727, -1.7279, 0.05, 1.5134, -0.198, 0.9043, 2.0298, -0.2513, 0.337, 0.6695]\n",
      "iteration: 121968\n",
      "w: [1.2312, 2.067, 4.9654, -1.9621, -1.7349, 0.05, 1.5049, -0.1987, 0.8927, 2.0593, -0.2224, 0.3607, 0.662]\n",
      "iteration: 137328\n",
      "w: [1.2312, 2.067, 4.9636, -1.9787, -1.7444, 0.05, 1.5047, -0.1892, 0.8902, 2.0542, -0.2281, 0.3667, 0.6568]\n",
      "iteration: 152688\n",
      "w: [1.2312, 2.067, 4.9629, -1.9773, -1.7454, 0.05, 1.499, -0.1956, 0.8844, 2.049, -0.2334, 0.3615, 0.6527]\n",
      "Loss in trainset: 0.3167\n",
      "Loss in testset: 0.2969\n",
      "TRAIN: 59696 TEST: 28455\n",
      "dataset built\n",
      "Loss in trainset: 0.3202\n",
      "Loss in testset: 0.3397\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f88fe970199f4c79b929d9468f053bd2",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "pre-train:   0%|          | 0/22374 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "w: [2.0143, 2.047, 5.0, -0.5, -0.5, 0.2, 1.4, -0.2, 0.8, 2.0, -0.2, 0.2, 1.0]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "04df05c0528c4e118ed2c0c8332d82ba",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "train:   0%|          | 0/156714 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loss in trainset: 0.3172\n",
      "Loss in testset: 0.3381\n",
      "iteration: 15360\n",
      "w: [2.1098, 2.1547, 5.1624, -1.3109, -1.2452, 0.05, 1.5603, -0.15, 0.9801, 2.0537, -0.1785, 0.2359, 1.1261]\n",
      "iteration: 30720\n",
      "w: [2.1147, 2.1603, 5.2114, -1.7705, -1.4815, 0.05, 1.5164, -0.1883, 0.9709, 2.0304, -0.2254, 0.3732, 1.0897]\n",
      "iteration: 46080\n",
      "w: [2.1149, 2.1605, 5.1015, -1.9801, -1.4999, 0.05, 1.4796, -0.1861, 0.9498, 1.9839, -0.283, 0.3439, 0.9421]\n",
      "Loss in trainset: 0.3037\n",
      "Loss in testset: 0.3244\n",
      "iteration: 60942\n",
      "w: [2.1149, 2.1605, 5.1075, -1.9231, -1.6885, 0.0635, 1.3861, -0.2296, 0.8601, 2.0228, -0.2517, 0.3458, 0.9562]\n",
      "iteration: 76302\n",
      "w: [2.1149, 2.1605, 5.024, -1.9369, -1.716, 0.05, 1.3839, -0.2055, 0.8635, 2.0164, -0.2617, 0.3731, 0.8707]\n",
      "iteration: 91662\n",
      "w: [2.1149, 2.1605, 4.8535, -1.8587, -1.6669, 0.05, 1.439, -0.1522, 0.9136, 2.0086, -0.2717, 0.3698, 0.809]\n",
      "Loss in trainset: 0.3030\n",
      "Loss in testset: 0.3238\n",
      "iteration: 106524\n",
      "w: [2.1149, 2.1605, 4.8535, -1.905, -1.6778, 0.05, 1.399, -0.1871, 0.8676, 2.0248, -0.2553, 0.383, 0.7918]\n",
      "iteration: 121884\n",
      "w: [2.1149, 2.1605, 4.8453, -1.9473, -1.6983, 0.05, 1.4095, -0.1723, 0.8757, 2.0325, -0.2472, 0.3812, 0.7653]\n",
      "iteration: 137244\n",
      "w: [2.1149, 2.1605, 4.8521, -1.9669, -1.7101, 0.05, 1.4014, -0.1741, 0.8658, 2.038, -0.2417, 0.3859, 0.7648]\n",
      "iteration: 152604\n",
      "w: [2.1149, 2.1605, 4.849, -1.9629, -1.7106, 0.05, 1.3997, -0.1763, 0.8638, 2.0348, -0.2448, 0.3832, 0.7608]\n",
      "Loss in trainset: 0.3030\n",
      "Loss in testset: 0.3237\n",
      "TRAIN: 59234 TEST: 28917\n",
      "dataset built\n",
      "Loss in trainset: 0.3255\n",
      "Loss in testset: 0.3286\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1a8d4bd1e6a441b5ab3dc4d86462a939",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "pre-train:   0%|          | 0/20916 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "w: [1.2804, 1.8287, 5.0, -0.5, -0.5, 0.2, 1.4, -0.2, 0.8, 2.0, -0.2, 0.2, 1.0]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "88b12e214c7244aaa85a1392eb067f98",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "train:   0%|          | 0/156786 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loss in trainset: 0.3233\n",
      "Loss in testset: 0.3258\n",
      "iteration: 15360\n",
      "w: [1.2103, 1.9125, 5.2223, -1.3239, -1.3125, 0.05, 1.5385, -0.1749, 0.9212, 2.0346, -0.1624, 0.3354, 1.0593]\n",
      "iteration: 30720\n",
      "w: [1.2066, 1.9168, 5.2443, -1.6266, -1.5494, 0.05, 1.4753, -0.1821, 0.8804, 1.9437, -0.264, 0.3369, 0.7392]\n",
      "iteration: 46080\n",
      "w: [1.2065, 1.917, 5.1167, -1.8355, -1.5635, 0.05, 1.4941, -0.1721, 0.8861, 1.9933, -0.2259, 0.3439, 0.6005]\n",
      "Loss in trainset: 0.3098\n",
      "Loss in testset: 0.3112\n",
      "iteration: 60966\n",
      "w: [1.2065, 1.917, 5.0007, -1.6979, -1.6784, 0.05, 1.4608, -0.1968, 0.8441, 2.0375, -0.1941, 0.3672, 0.5359]\n",
      "iteration: 76326\n",
      "w: [1.2065, 1.917, 4.9066, -1.7258, -1.6968, 0.05, 1.4394, -0.2106, 0.8168, 2.0294, -0.2062, 0.3273, 0.547]\n",
      "iteration: 91686\n",
      "w: [1.2065, 1.917, 4.8547, -1.8015, -1.7653, 0.05, 1.4972, -0.158, 0.8681, 2.0529, -0.1808, 0.3349, 0.5057]\n",
      "Loss in trainset: 0.3095\n",
      "Loss in testset: 0.3109\n",
      "iteration: 106572\n",
      "w: [1.2065, 1.917, 4.8316, -1.859, -1.766, 0.0548, 1.5013, -0.167, 0.8685, 2.039, -0.1959, 0.3344, 0.437]\n",
      "iteration: 121932\n",
      "w: [1.2065, 1.917, 4.8202, -1.877, -1.7833, 0.05, 1.4866, -0.1863, 0.8516, 2.0365, -0.1985, 0.3419, 0.4129]\n",
      "iteration: 137292\n",
      "w: [1.2065, 1.917, 4.8332, -1.9048, -1.8033, 0.05, 1.4775, -0.1907, 0.8413, 2.0437, -0.191, 0.3511, 0.4094]\n",
      "iteration: 152652\n",
      "w: [1.2065, 1.917, 4.8312, -1.9055, -1.8043, 0.05, 1.4762, -0.1916, 0.8397, 2.0418, -0.193, 0.3512, 0.4082]\n",
      "Loss in trainset: 0.3094\n",
      "Loss in testset: 0.3109\n",
      "\n",
      "Training finished!\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lr: float = 4e-2\n",
    "n_epoch: int = 3\n",
    "n_splits: int = 3\n",
    "batch_size: int = 512\n",
    "verbose: bool = True\n",
    "\n",
    "dataset = pd.read_csv(\"./revlog_history.tsv\", sep='\\t', index_col=None, dtype={'r_history': str ,'t_history': str} )\n",
    "dataset = dataset[(dataset['i'] > 1) & (dataset['delta_t'] > 0) & (dataset['t_history'].str.count(',0') == 0)]\n",
    "if dataset.empty:\n",
    "    raise ValueError('Training data is inadequate.')\n",
    "dataset['tensor'] = dataset.progress_apply(lambda x: lineToTensor(list(zip([x['t_history']], [x['r_history']]))[0]), axis=1)\n",
    "dataset['group'] = dataset['r_history'] + dataset['t_history']\n",
    "print(\"Tensorized!\")\n",
    "\n",
    "n_pre_train_groups = len(dataset[dataset['i'] == 2]['group'].unique())\n",
    "if n_pre_train_groups < n_splits:\n",
    "    print(\"Not enough groups for pre-training. Splitting into {} folds.\".format(n_pre_train_groups))\n",
    "    n_splits = n_pre_train_groups\n",
    "\n",
    "w = []\n",
    "plots = []\n",
    "if n_splits > 1:\n",
    "    sgkf = StratifiedGroupKFold(n_splits=n_splits)\n",
    "    for train_index, test_index in sgkf.split(dataset, dataset['i'], dataset['group']):\n",
    "        print(\"TRAIN:\", len(train_index), \"TEST:\",  len(test_index))\n",
    "        train_set = dataset.iloc[train_index].copy()\n",
    "        test_set = dataset.iloc[test_index].copy()\n",
    "        trainer = Trainer(train_set, test_set, init_w, n_epoch=n_epoch, lr=lr, batch_size=batch_size)\n",
    "        w.append(trainer.train(verbose=verbose))\n",
    "        plots.append(trainer.plot())\n",
    "else:\n",
    "    trainer = Trainer(dataset, dataset, init_w, n_epoch=n_epoch, lr=lr, batch_size=batch_size)\n",
    "    w.append(trainer.train(verbose=verbose))\n",
    "    plots.append(trainer.plot())\n",
    "\n",
    "w = np.array(w)\n",
    "avg_w = np.round(np.mean(w, axis=0), 4)\n",
    "w = avg_w.tolist()\n",
    "print(\"\\nTraining finished!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1.5175, 2.0482, 4.8809, -1.9485, -1.7534, 0.05, 1.4583, -0.1878, 0.8626, 2.0418, -0.2238, 0.3652, 0.6071]\n",
      "1:again, 2:hard, 3:good, 4:easy\n",
      "\n",
      "first rating: 1\n",
      "rating history: 1,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,2d,3d,6d,10d,18d,1.0m,1.7m,2.7m,4.4m,6.8m\n",
      "difficulty history: 0,8.8,8.6,8.4,8.2,8.1,7.9,7.7,7.6,7.5,7.3\n",
      "\n",
      "first rating: 2\n",
      "rating history: 2,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,4d,9d,19d,1.3m,2.4m,4.3m,7.4m,1.0y,1.6y,2.6y\n",
      "difficulty history: 0,6.8,6.7,6.6,6.6,6.5,6.4,6.3,6.2,6.2,6.1\n",
      "\n",
      "first rating: 3\n",
      "rating history: 3,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,6d,16d,1.3m,2.8m,5.7m,10.8m,1.6y,2.7y,4.5y,7.2y\n",
      "difficulty history: 0,4.9,4.9,4.9,4.9,4.9,4.9,4.9,4.9,4.9,4.9\n",
      "\n",
      "first rating: 4\n",
      "rating history: 4,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,8d,24d,2.2m,5.1m,11.1m,1.8y,3.4y,6.0y,10.0y,16.1y\n",
      "difficulty history: 0,2.9,3.0,3.1,3.2,3.3,3.4,3.4,3.5,3.6,3.7\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(w)\n",
    "\n",
    "class Collection:\n",
    "    def __init__(self, w: List[float]) -> None:\n",
    "        self.model = FSRS(w)\n",
    "        self.model.eval()\n",
    "\n",
    "    def predict(self, t_history: str, r_history: str):\n",
    "        with torch.no_grad():\n",
    "            line_tensor = lineToTensor(list(zip([t_history], [r_history]))[0]).unsqueeze(1)\n",
    "            output_t = self.model(line_tensor)\n",
    "            return output_t[-1][0]\n",
    "\n",
    "    def batch_predict(self, dataset):\n",
    "        fast_dataset = RevlogDataset(dataset)\n",
    "        with torch.no_grad():\n",
    "            outputs, _ = self.model(fast_dataset.x_train.transpose(0, 1))\n",
    "            stabilities, difficulties = outputs[fast_dataset.seq_len-1, torch.arange(len(fast_dataset))].transpose(0, 1)\n",
    "            return stabilities.tolist(), difficulties.tolist()\n",
    "        \n",
    "requestRetention = 0.9\n",
    "\n",
    "my_collection = Collection(w)\n",
    "preview_text = \"1:again, 2:hard, 3:good, 4:easy\\n\"\n",
    "for first_rating in (1,2,3,4):\n",
    "    preview_text += f'\\nfirst rating: {first_rating}\\n'\n",
    "    t_history = \"0\"\n",
    "    d_history = \"0\"\n",
    "    r_history = f\"{first_rating}\"  # the first rating of the new card\n",
    "    # print(\"stability, difficulty, lapses\")\n",
    "    for i in range(10):\n",
    "        states = my_collection.predict(t_history, r_history)\n",
    "        # print('{0:9.2f} {1:11.2f} {2:7.0f}'.format(\n",
    "            # *list(map(lambda x: round(float(x), 4), states))))\n",
    "        next_t = max(round(float(np.log(requestRetention)/np.log(0.9) * states[0])), 1)\n",
    "        difficulty = round(float(states[1]), 1)\n",
    "        t_history += f',{int(next_t)}'\n",
    "        d_history += f',{difficulty}'\n",
    "        r_history += f\",3\"\n",
    "    preview_text += f\"rating history: {r_history}\\n\"\n",
    "    preview_text += \"interval history: \" + \",\".join([f\"{ivl}d\" if ivl < 30 else f\"{ivl / 30:.1f}m\" if ivl < 365 else f\"{ivl / 365:.1f}y\" for ivl in map(int, t_history.split(','))]) + \"\\n\"\n",
    "    preview_text += f\"difficulty history: {d_history}\\n\"\n",
    "print(preview_text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([5.6139, 4.8809])\n",
      "tensor([15.8899,  4.8809])\n",
      "tensor([38.4434,  4.8809])\n",
      "tensor([83.8271,  4.8809])\n",
      "tensor([170.4739,   4.8809])\n",
      "tensor([8.8441, 8.2124])\n",
      "tensor([ 2.8757, 10.0000])\n",
      "tensor([4.0717, 9.7440])\n",
      "tensor([5.8560, 9.5009])\n",
      "tensor([8.7398, 9.2699])\n",
      "tensor([13.2609,  9.0504])\n",
      "tensor([19.9486,  8.8420])\n",
      "rating history: 3,3,3,3,3,1,1,3,3,3,3,3\n",
      "interval history: 0,6,16,38,84,170,9,3,4,6,9,13,20\n",
      "difficulty history: 0,4.9,4.9,4.9,4.9,4.9,8.2,10.0,9.7,9.5,9.3,9.1,8.8\n"
     ]
    }
   ],
   "source": [
    "test_rating_sequence = \"3,3,3,3,3,1,1,3,3,3,3,3\"\n",
    "requestRetention = 0.9  # recommended setting: 0.8 ~ 0.9\n",
    "easyBonus = 1.3\n",
    "hardInterval = 1.2\n",
    "\n",
    "t_history = \"0\"\n",
    "d_history = \"0\"\n",
    "for i in range(len(test_rating_sequence.split(','))):\n",
    "    rating = test_rating_sequence[2*i]\n",
    "    last_t = int(t_history.split(',')[-1])\n",
    "    r_history = test_rating_sequence[:2*i+1]\n",
    "    states = my_collection.predict(t_history, r_history)\n",
    "    print(states)\n",
    "    next_t = max(1,round(float(np.log(requestRetention)/np.log(0.9) * states[0])))\n",
    "    if rating == '4':\n",
    "        next_t = round(next_t * easyBonus)\n",
    "    elif rating == '2':\n",
    "        next_t = round(last_t * hardInterval)\n",
    "    t_history += f',{int(next_t)}'\n",
    "    difficulty = round(float(states[1]), 1)\n",
    "    d_history += f',{difficulty}'\n",
    "preview_text = f\"rating history: {test_rating_sequence}\\n\"\n",
    "preview_text += f\"interval history: {t_history}\\n\"\n",
    "preview_text += f\"difficulty history: {d_history}\"\n",
    "print(preview_text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loss before: 0.3265, loss after: 0.3097, improvement: 0.0169\n"
     ]
    }
   ],
   "source": [
    "my_collection = Collection(init_w)\n",
    "stabilities, difficulties = my_collection.batch_predict(dataset)\n",
    "dataset['stability'] = stabilities\n",
    "dataset['difficulty'] = difficulties\n",
    "dataset['p'] = np.exp(np.log(0.9) * dataset['delta_t'] / dataset['stability'])\n",
    "dataset['log_loss'] = dataset.apply(lambda row: - np.log(row['p']) if row['y'] == 1 else - np.log(1 - row['p']), axis=1)\n",
    "loss_before = dataset['log_loss'].mean()\n",
    "\n",
    "my_collection = Collection(w)\n",
    "stabilities, difficulties = my_collection.batch_predict(dataset)\n",
    "dataset['stability'] = stabilities\n",
    "dataset['difficulty'] = difficulties\n",
    "dataset['p'] = np.exp(np.log(0.9) * dataset['delta_t'] / dataset['stability'])\n",
    "dataset['log_loss'] = dataset.apply(lambda row: - np.log(row['p']) if row['y'] == 1 else - np.log(1 - row['p']), axis=1)\n",
    "loss_after = dataset['log_loss'].mean()\n",
    "\n",
    "tmp = dataset.copy()\n",
    "tmp['stability'] = tmp['stability'].map(lambda x: round(x, 2))\n",
    "tmp['difficulty'] = tmp['difficulty'].map(lambda x: round(x, 2))\n",
    "tmp['p'] = tmp['p'].map(lambda x: round(x, 2))\n",
    "tmp['log_loss'] = tmp['log_loss'].map(lambda x: round(x, 2))\n",
    "tmp.rename(columns={\"r\": \"grade\", \"p\": \"retrievability\"}, inplace=True)\n",
    "tmp[['id', 'cid', 'review_date', 'r_history', 't_history', 'delta_t', 'grade', 'stability', 'difficulty', 'retrievability', 'log_loss']].to_csv(\"./evaluation.tsv\", sep='\\t', index=False)\n",
    "del tmp\n",
    "print(f\"loss before: {loss_before:.4f}, loss after: {loss_after:.4f}, improvement: {loss_before - loss_after:.4f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R-squared: 0.9290\n",
      "RMSE: 0.0188\n",
      "[0.09840693 0.89082522]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Last rating: 1\n",
      "R-squared: 0.2391\n",
      "RMSE: 0.0497\n",
      "[0.31799184 0.62477926]\n",
      "\n",
      "Last rating: 2\n",
      "R-squared: -0.6794\n",
      "RMSE: 0.0959\n",
      "[-0.59903329  1.55099809]\n",
      "\n",
      "Last rating: 3\n",
      "R-squared: 0.9287\n",
      "RMSE: 0.0208\n",
      "[0.0432517  0.96468574]\n",
      "\n",
      "Last rating: 4\n",
      "R-squared: -0.3199\n",
      "RMSE: 0.0379\n",
      "[0.48024312 0.51202574]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1600x1200 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# code from https://github.com/papousek/duolingo-halflife-regression/blob/master/evaluation.py\n",
    "def load_brier(predictions, real, bins=20):\n",
    "    counts = np.zeros(bins)\n",
    "    correct = np.zeros(bins)\n",
    "    prediction = np.zeros(bins)\n",
    "    for p, r in zip(predictions, real):\n",
    "        bin = min(int(p * bins), bins - 1)\n",
    "        counts[bin] += 1\n",
    "        correct[bin] += r\n",
    "        prediction[bin] += p\n",
    "    np.seterr(invalid='ignore')\n",
    "    prediction_means = prediction / counts\n",
    "    prediction_means[np.isnan(prediction_means)] = ((np.arange(bins) + 0.5) / bins)[np.isnan(prediction_means)]\n",
    "    correct_means = correct / counts\n",
    "    correct_means[np.isnan(correct_means)] = 0\n",
    "    size = len(predictions)\n",
    "    answer_mean = sum(correct) / size\n",
    "    return {\n",
    "        \"reliability\": sum(counts * (correct_means - prediction_means) ** 2) / size,\n",
    "        \"resolution\": sum(counts * (correct_means - answer_mean) ** 2) / size,\n",
    "        \"uncertainty\": answer_mean * (1 - answer_mean),\n",
    "        \"detail\": {\n",
    "            \"bin_count\": bins,\n",
    "            \"bin_counts\": list(counts),\n",
    "            \"bin_prediction_means\": list(prediction_means),\n",
    "            \"bin_correct_means\": list(correct_means),\n",
    "        }\n",
    "    }\n",
    "\n",
    "\n",
    "def plot_brier(predictions, real, bins=20):\n",
    "    brier = load_brier(predictions, real, bins=bins)\n",
    "    bin_prediction_means = brier['detail']['bin_prediction_means']\n",
    "    bin_correct_means = brier['detail']['bin_correct_means']\n",
    "    bin_counts = brier['detail']['bin_counts']\n",
    "    r2 = r2_score(bin_correct_means, bin_prediction_means, sample_weight=bin_counts)\n",
    "    rmse = mean_squared_error(bin_correct_means, bin_prediction_means, sample_weight=bin_counts, squared=False)\n",
    "    print(f\"R-squared: {r2:.4f}\")\n",
    "    print(f\"RMSE: {rmse:.4f}\")\n",
    "    ax = plt.gca()\n",
    "    ax.set_xlim([0, 1])\n",
    "    ax.set_ylim([0, 1])\n",
    "    plt.grid(True)\n",
    "    fit_wls = sm.WLS(bin_correct_means, sm.add_constant(bin_prediction_means), weights=bin_counts).fit()\n",
    "    print(fit_wls.params)\n",
    "    y_regression = [fit_wls.params[0] + fit_wls.params[1]*x for x in bin_prediction_means]\n",
    "    plt.plot(bin_prediction_means, y_regression, label='Weighted Least Squares Regression', color=\"green\")\n",
    "    plt.plot(bin_prediction_means, bin_correct_means, label='Actual Calibration', color=\"#1f77b4\")\n",
    "    plt.plot((0, 1), (0, 1), label='Perfect Calibration', color=\"#ff7f0e\")\n",
    "    bin_count = brier['detail']['bin_count']\n",
    "    counts = np.array(bin_counts)\n",
    "    bins = (np.arange(bin_count) + 0.5) / bin_count\n",
    "    plt.legend(loc='upper center')\n",
    "    plt.xlabel('Predicted R')\n",
    "    plt.ylabel('Actual R')\n",
    "    plt.twinx()\n",
    "    plt.ylabel('Number of reviews')\n",
    "    plt.bar(bins, counts, width=(0.8 / bin_count), ec='k', lw=.2, alpha=0.5, label='Number of reviews')\n",
    "    plt.legend(loc='lower center')\n",
    "\n",
    "\n",
    "plot_brier(dataset['p'], dataset['y'], bins=40)\n",
    "plt.show()\n",
    "plt.figure(figsize=(16, 12))\n",
    "for last_rating in (\"1\",\"2\",\"3\",\"4\"):\n",
    "    plt.subplot(2, 2, int(last_rating))\n",
    "    print(f\"\\nLast rating: {last_rating}\")\n",
    "    plot_brier(dataset[dataset['r_history'].str.endswith(last_rating)]['p'], dataset[dataset['r_history'].str.endswith(last_rating)]['y'], bins=40)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def to_percent(temp, position):\n",
    "    return '%1.0f' % (100 * temp) + '%'\n",
    "\n",
    "fig = plt.figure(1)\n",
    "ax1 = fig.add_subplot(111)\n",
    "ax2 = ax1.twinx()\n",
    "lns = []\n",
    "\n",
    "stability_calibration = pd.DataFrame(columns=['stability', 'predicted_retention', 'actual_retention'])\n",
    "stability_calibration = dataset[['stability', 'p', 'y']].copy()\n",
    "stability_calibration['bin'] = stability_calibration['stability'].map(lambda x: math.pow(1.2, math.floor(math.log(x, 1.2))))\n",
    "stability_group = stability_calibration.groupby('bin').count()\n",
    "\n",
    "lns1 = ax1.bar(x=stability_group.index, height=stability_group['y'], width=stability_group.index / 5.5,\n",
    "                ec='k', lw=.2, label='Number of predictions', alpha=0.5)\n",
    "ax1.set_ylabel(\"Number of predictions\")\n",
    "ax1.set_xlabel(\"Stability (days)\")\n",
    "ax1.semilogx()\n",
    "lns.append(lns1)\n",
    "\n",
    "stability_group = stability_calibration.groupby(by='bin').agg('mean')\n",
    "lns2 = ax2.plot(stability_group['y'], label='Actual retention')\n",
    "lns3 = ax2.plot(stability_group['p'], label='Predicted retention')\n",
    "ax2.set_ylabel(\"Retention\")\n",
    "ax2.set_ylim(0, 1)\n",
    "lns.append(lns2[0])\n",
    "lns.append(lns3[0])\n",
    "\n",
    "labs = [l.get_label() for l in lns]\n",
    "ax2.legend(lns, labs, loc='lower right')\n",
    "plt.grid(linestyle='--')\n",
    "plt.gca().yaxis.set_major_formatter(ticker.FuncFormatter(to_percent))\n",
    "plt.gca().xaxis.set_major_formatter(ticker.FormatStrFormatter('%d'))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(1)\n",
    "ax1 = fig.add_subplot(111)\n",
    "ax2 = ax1.twinx()\n",
    "lns = []\n",
    "\n",
    "difficulty_calibration = pd.DataFrame(columns=['difficulty', 'predicted_retention', 'actual_retention'])\n",
    "difficulty_calibration = dataset[['difficulty', 'p', 'y']].copy()\n",
    "difficulty_calibration['bin'] = difficulty_calibration['difficulty'].map(round)\n",
    "difficulty_group = difficulty_calibration.groupby('bin').count()\n",
    "\n",
    "lns1 = ax1.bar(x=difficulty_group.index, height=difficulty_group['y'],\n",
    "                ec='k', lw=.2, label='Number of predictions', alpha=0.5)\n",
    "ax1.set_ylabel(\"Number of predictions\")\n",
    "ax1.set_xlabel(\"Difficulty\")\n",
    "lns.append(lns1)\n",
    "\n",
    "difficulty_group = difficulty_calibration.groupby(by='bin').agg('mean')\n",
    "lns2 = ax2.plot(difficulty_group['y'], label='Actual retention')\n",
    "lns3 = ax2.plot(difficulty_group['p'], label='Predicted retention')\n",
    "ax2.set_ylabel(\"Retention\")\n",
    "ax2.set_ylim(0, 1)\n",
    "lns.append(lns2[0])\n",
    "lns.append(lns3[0])\n",
    "\n",
    "labs = [l.get_label() for l in lns]\n",
    "ax2.legend(lns, labs, loc='lower right')\n",
    "plt.grid(linestyle='--')\n",
    "plt.gca().yaxis.set_major_formatter(ticker.FuncFormatter(to_percent))\n",
    "plt.gca().xaxis.set_major_formatter(ticker.FormatStrFormatter('%d'))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "#T_9d2d4_row5_col2 {\n",
       "  background-color: #b1b1ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_9d2d4_row5_col3, #T_9d2d4_row7_col4 {\n",
       "  background-color: #ffeded;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_9d2d4_row5_col5 {\n",
       "  background-color: #c9c9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_9d2d4_row5_col6, #T_9d2d4_row11_col2 {\n",
       "  background-color: #ffc5c5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_9d2d4_row6_col1 {\n",
       "  background-color: #c5c5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_9d2d4_row6_col3 {\n",
       "  background-color: #ff7171;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_9d2d4_row6_col4 {\n",
       "  background-color: #f5f5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_9d2d4_row6_col5, #T_9d2d4_row10_col5 {\n",
       "  background-color: #ffd5d5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_9d2d4_row7_col1, #T_9d2d4_row10_col1 {\n",
       "  background-color: #e9e9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_9d2d4_row7_col2, #T_9d2d4_row9_col1 {\n",
       "  background-color: #ffe9e9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_9d2d4_row7_col3 {\n",
       "  background-color: #ffa5a5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_9d2d4_row7_col5 {\n",
       "  background-color: #ffcdcd;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_9d2d4_row7_col6, #T_9d2d4_row8_col6 {\n",
       "  background-color: #ff1919;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_9d2d4_row8_col0, #T_9d2d4_row9_col0, #T_9d2d4_row12_col0 {\n",
       "  background-color: #c1c1ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_9d2d4_row8_col2, #T_9d2d4_row10_col2, #T_9d2d4_row11_col4 {\n",
       "  background-color: #fff1f1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_9d2d4_row8_col3, #T_9d2d4_row12_col4 {\n",
       "  background-color: #fdfdff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_9d2d4_row8_col4, #T_9d2d4_row9_col2 {\n",
       "  background-color: #ffc9c9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_9d2d4_row9_col3 {\n",
       "  background-color: #ffb9b9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_9d2d4_row9_col4 {\n",
       "  background-color: #fff5f5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_9d2d4_row9_col6, #T_9d2d4_row11_col3 {\n",
       "  background-color: #ff5959;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_9d2d4_row10_col0, #T_9d2d4_row13_col2 {\n",
       "  background-color: #b5b5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_9d2d4_row10_col3 {\n",
       "  background-color: #ff7575;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_9d2d4_row10_col4 {\n",
       "  background-color: #ffe1e1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_9d2d4_row10_col6 {\n",
       "  background-color: #ff0505;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_9d2d4_row11_col5, #T_9d2d4_row13_col0 {\n",
       "  background-color: #9191ff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_9d2d4_row12_col1 {\n",
       "  background-color: #adadff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_9d2d4_row12_col2 {\n",
       "  background-color: #ffd1d1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_9d2d4_row13_col1 {\n",
       "  background-color: #7d7dff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_9d2d4_row14_col1 {\n",
       "  background-color: #a1a1ff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_9d2d4\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >d_bin</th>\n",
       "      <th id=\"T_9d2d4_level0_col0\" class=\"col_heading level0 col0\" >3</th>\n",
       "      <th id=\"T_9d2d4_level0_col1\" class=\"col_heading level0 col1\" >5</th>\n",
       "      <th id=\"T_9d2d4_level0_col2\" class=\"col_heading level0 col2\" >6</th>\n",
       "      <th id=\"T_9d2d4_level0_col3\" class=\"col_heading level0 col3\" >7</th>\n",
       "      <th id=\"T_9d2d4_level0_col4\" class=\"col_heading level0 col4\" >8</th>\n",
       "      <th id=\"T_9d2d4_level0_col5\" class=\"col_heading level0 col5\" >9</th>\n",
       "      <th id=\"T_9d2d4_level0_col6\" class=\"col_heading level0 col6\" >10</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >s_bin</th>\n",
       "      <th class=\"blank col0\" >&nbsp;</th>\n",
       "      <th class=\"blank col1\" >&nbsp;</th>\n",
       "      <th class=\"blank col2\" >&nbsp;</th>\n",
       "      <th class=\"blank col3\" >&nbsp;</th>\n",
       "      <th class=\"blank col4\" >&nbsp;</th>\n",
       "      <th class=\"blank col5\" >&nbsp;</th>\n",
       "      <th class=\"blank col6\" >&nbsp;</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_9d2d4_level0_row0\" class=\"row_heading level0 row0\" >1.400000</th>\n",
       "      <td id=\"T_9d2d4_row0_col0\" class=\"data row0 col0\" ></td>\n",
       "      <td id=\"T_9d2d4_row0_col1\" class=\"data row0 col1\" ></td>\n",
       "      <td id=\"T_9d2d4_row0_col2\" class=\"data row0 col2\" ></td>\n",
       "      <td id=\"T_9d2d4_row0_col3\" class=\"data row0 col3\" ></td>\n",
       "      <td id=\"T_9d2d4_row0_col4\" class=\"data row0 col4\" ></td>\n",
       "      <td id=\"T_9d2d4_row0_col5\" class=\"data row0 col5\" >2.59%</td>\n",
       "      <td id=\"T_9d2d4_row0_col6\" class=\"data row0 col6\" >2.92%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_9d2d4_level0_row1\" class=\"row_heading level0 row1\" >1.960000</th>\n",
       "      <td id=\"T_9d2d4_row1_col0\" class=\"data row1 col0\" ></td>\n",
       "      <td id=\"T_9d2d4_row1_col1\" class=\"data row1 col1\" ></td>\n",
       "      <td id=\"T_9d2d4_row1_col2\" class=\"data row1 col2\" ></td>\n",
       "      <td id=\"T_9d2d4_row1_col3\" class=\"data row1 col3\" ></td>\n",
       "      <td id=\"T_9d2d4_row1_col4\" class=\"data row1 col4\" >3.29%</td>\n",
       "      <td id=\"T_9d2d4_row1_col5\" class=\"data row1 col5\" >-4.90%</td>\n",
       "      <td id=\"T_9d2d4_row1_col6\" class=\"data row1 col6\" >0.01%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_9d2d4_level0_row2\" class=\"row_heading level0 row2\" >2.740000</th>\n",
       "      <td id=\"T_9d2d4_row2_col0\" class=\"data row2 col0\" ></td>\n",
       "      <td id=\"T_9d2d4_row2_col1\" class=\"data row2 col1\" ></td>\n",
       "      <td id=\"T_9d2d4_row2_col2\" class=\"data row2 col2\" ></td>\n",
       "      <td id=\"T_9d2d4_row2_col3\" class=\"data row2 col3\" >5.14%</td>\n",
       "      <td id=\"T_9d2d4_row2_col4\" class=\"data row2 col4\" >-1.44%</td>\n",
       "      <td id=\"T_9d2d4_row2_col5\" class=\"data row2 col5\" >0.13%</td>\n",
       "      <td id=\"T_9d2d4_row2_col6\" class=\"data row2 col6\" >0.01%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_9d2d4_level0_row3\" class=\"row_heading level0 row3\" >3.840000</th>\n",
       "      <td id=\"T_9d2d4_row3_col0\" class=\"data row3 col0\" ></td>\n",
       "      <td id=\"T_9d2d4_row3_col1\" class=\"data row3 col1\" ></td>\n",
       "      <td id=\"T_9d2d4_row3_col2\" class=\"data row3 col2\" ></td>\n",
       "      <td id=\"T_9d2d4_row3_col3\" class=\"data row3 col3\" >-1.03%</td>\n",
       "      <td id=\"T_9d2d4_row3_col4\" class=\"data row3 col4\" >-1.95%</td>\n",
       "      <td id=\"T_9d2d4_row3_col5\" class=\"data row3 col5\" >-3.87%</td>\n",
       "      <td id=\"T_9d2d4_row3_col6\" class=\"data row3 col6\" >1.01%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_9d2d4_level0_row4\" class=\"row_heading level0 row4\" >5.380000</th>\n",
       "      <td id=\"T_9d2d4_row4_col0\" class=\"data row4 col0\" ></td>\n",
       "      <td id=\"T_9d2d4_row4_col1\" class=\"data row4 col1\" >-1.05%</td>\n",
       "      <td id=\"T_9d2d4_row4_col2\" class=\"data row4 col2\" ></td>\n",
       "      <td id=\"T_9d2d4_row4_col3\" class=\"data row4 col3\" >-0.59%</td>\n",
       "      <td id=\"T_9d2d4_row4_col4\" class=\"data row4 col4\" >-1.80%</td>\n",
       "      <td id=\"T_9d2d4_row4_col5\" class=\"data row4 col5\" >-2.60%</td>\n",
       "      <td id=\"T_9d2d4_row4_col6\" class=\"data row4 col6\" >0.23%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_9d2d4_level0_row5\" class=\"row_heading level0 row5\" >7.530000</th>\n",
       "      <td id=\"T_9d2d4_row5_col0\" class=\"data row5 col0\" >-1.41%</td>\n",
       "      <td id=\"T_9d2d4_row5_col1\" class=\"data row5 col1\" >-1.47%</td>\n",
       "      <td id=\"T_9d2d4_row5_col2\" class=\"data row5 col2\" >-3.05%</td>\n",
       "      <td id=\"T_9d2d4_row5_col3\" class=\"data row5 col3\" >0.72%</td>\n",
       "      <td id=\"T_9d2d4_row5_col4\" class=\"data row5 col4\" >-0.56%</td>\n",
       "      <td id=\"T_9d2d4_row5_col5\" class=\"data row5 col5\" >-2.16%</td>\n",
       "      <td id=\"T_9d2d4_row5_col6\" class=\"data row5 col6\" >2.32%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_9d2d4_level0_row6\" class=\"row_heading level0 row6\" >10.540000</th>\n",
       "      <td id=\"T_9d2d4_row6_col0\" class=\"data row6 col0\" >-1.51%</td>\n",
       "      <td id=\"T_9d2d4_row6_col1\" class=\"data row6 col1\" >-2.19%</td>\n",
       "      <td id=\"T_9d2d4_row6_col2\" class=\"data row6 col2\" ></td>\n",
       "      <td id=\"T_9d2d4_row6_col3\" class=\"data row6 col3\" >5.60%</td>\n",
       "      <td id=\"T_9d2d4_row6_col4\" class=\"data row6 col4\" >-0.33%</td>\n",
       "      <td id=\"T_9d2d4_row6_col5\" class=\"data row6 col5\" >1.66%</td>\n",
       "      <td id=\"T_9d2d4_row6_col6\" class=\"data row6 col6\" >5.02%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_9d2d4_level0_row7\" class=\"row_heading level0 row7\" >14.760000</th>\n",
       "      <td id=\"T_9d2d4_row7_col0\" class=\"data row7 col0\" >-1.95%</td>\n",
       "      <td id=\"T_9d2d4_row7_col1\" class=\"data row7 col1\" >-0.91%</td>\n",
       "      <td id=\"T_9d2d4_row7_col2\" class=\"data row7 col2\" >0.90%</td>\n",
       "      <td id=\"T_9d2d4_row7_col3\" class=\"data row7 col3\" >3.48%</td>\n",
       "      <td id=\"T_9d2d4_row7_col4\" class=\"data row7 col4\" >0.64%</td>\n",
       "      <td id=\"T_9d2d4_row7_col5\" class=\"data row7 col5\" >1.92%</td>\n",
       "      <td id=\"T_9d2d4_row7_col6\" class=\"data row7 col6\" >9.03%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_9d2d4_level0_row8\" class=\"row_heading level0 row8\" >20.660000</th>\n",
       "      <td id=\"T_9d2d4_row8_col0\" class=\"data row8 col0\" >-2.47%</td>\n",
       "      <td id=\"T_9d2d4_row8_col1\" class=\"data row8 col1\" >-1.75%</td>\n",
       "      <td id=\"T_9d2d4_row8_col2\" class=\"data row8 col2\" >0.55%</td>\n",
       "      <td id=\"T_9d2d4_row8_col3\" class=\"data row8 col3\" >-0.03%</td>\n",
       "      <td id=\"T_9d2d4_row8_col4\" class=\"data row8 col4\" >2.18%</td>\n",
       "      <td id=\"T_9d2d4_row8_col5\" class=\"data row8 col5\" >2.94%</td>\n",
       "      <td id=\"T_9d2d4_row8_col6\" class=\"data row8 col6\" >8.95%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_9d2d4_level0_row9\" class=\"row_heading level0 row9\" >28.930000</th>\n",
       "      <td id=\"T_9d2d4_row9_col0\" class=\"data row9 col0\" >-2.38%</td>\n",
       "      <td id=\"T_9d2d4_row9_col1\" class=\"data row9 col1\" >0.91%</td>\n",
       "      <td id=\"T_9d2d4_row9_col2\" class=\"data row9 col2\" >2.14%</td>\n",
       "      <td id=\"T_9d2d4_row9_col3\" class=\"data row9 col3\" >2.71%</td>\n",
       "      <td id=\"T_9d2d4_row9_col4\" class=\"data row9 col4\" >0.34%</td>\n",
       "      <td id=\"T_9d2d4_row9_col5\" class=\"data row9 col5\" >2.56%</td>\n",
       "      <td id=\"T_9d2d4_row9_col6\" class=\"data row9 col6\" >6.49%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_9d2d4_level0_row10\" class=\"row_heading level0 row10\" >40.500000</th>\n",
       "      <td id=\"T_9d2d4_row10_col0\" class=\"data row10 col0\" >-2.96%</td>\n",
       "      <td id=\"T_9d2d4_row10_col1\" class=\"data row10 col1\" >-0.81%</td>\n",
       "      <td id=\"T_9d2d4_row10_col2\" class=\"data row10 col2\" >0.52%</td>\n",
       "      <td id=\"T_9d2d4_row10_col3\" class=\"data row10 col3\" >5.46%</td>\n",
       "      <td id=\"T_9d2d4_row10_col4\" class=\"data row10 col4\" >1.18%</td>\n",
       "      <td id=\"T_9d2d4_row10_col5\" class=\"data row10 col5\" >1.72%</td>\n",
       "      <td id=\"T_9d2d4_row10_col6\" class=\"data row10 col6\" >9.84%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_9d2d4_level0_row11\" class=\"row_heading level0 row11\" >56.690000</th>\n",
       "      <td id=\"T_9d2d4_row11_col0\" class=\"data row11 col0\" >-1.47%</td>\n",
       "      <td id=\"T_9d2d4_row11_col1\" class=\"data row11 col1\" >-1.05%</td>\n",
       "      <td id=\"T_9d2d4_row11_col2\" class=\"data row11 col2\" >2.25%</td>\n",
       "      <td id=\"T_9d2d4_row11_col3\" class=\"data row11 col3\" >6.55%</td>\n",
       "      <td id=\"T_9d2d4_row11_col4\" class=\"data row11 col4\" >0.55%</td>\n",
       "      <td id=\"T_9d2d4_row11_col5\" class=\"data row11 col5\" >-4.36%</td>\n",
       "      <td id=\"T_9d2d4_row11_col6\" class=\"data row11 col6\" ></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_9d2d4_level0_row12\" class=\"row_heading level0 row12\" >79.370000</th>\n",
       "      <td id=\"T_9d2d4_row12_col0\" class=\"data row12 col0\" >-2.47%</td>\n",
       "      <td id=\"T_9d2d4_row12_col1\" class=\"data row12 col1\" >-3.25%</td>\n",
       "      <td id=\"T_9d2d4_row12_col2\" class=\"data row12 col2\" >1.77%</td>\n",
       "      <td id=\"T_9d2d4_row12_col3\" class=\"data row12 col3\" ></td>\n",
       "      <td id=\"T_9d2d4_row12_col4\" class=\"data row12 col4\" >-0.03%</td>\n",
       "      <td id=\"T_9d2d4_row12_col5\" class=\"data row12 col5\" ></td>\n",
       "      <td id=\"T_9d2d4_row12_col6\" class=\"data row12 col6\" ></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_9d2d4_level0_row13\" class=\"row_heading level0 row13\" >111.120000</th>\n",
       "      <td id=\"T_9d2d4_row13_col0\" class=\"data row13 col0\" >-4.24%</td>\n",
       "      <td id=\"T_9d2d4_row13_col1\" class=\"data row13 col1\" >-5.03%</td>\n",
       "      <td id=\"T_9d2d4_row13_col2\" class=\"data row13 col2\" >-2.88%</td>\n",
       "      <td id=\"T_9d2d4_row13_col3\" class=\"data row13 col3\" ></td>\n",
       "      <td id=\"T_9d2d4_row13_col4\" class=\"data row13 col4\" ></td>\n",
       "      <td id=\"T_9d2d4_row13_col5\" class=\"data row13 col5\" ></td>\n",
       "      <td id=\"T_9d2d4_row13_col6\" class=\"data row13 col6\" ></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_9d2d4_level0_row14\" class=\"row_heading level0 row14\" >155.570000</th>\n",
       "      <td id=\"T_9d2d4_row14_col0\" class=\"data row14 col0\" ></td>\n",
       "      <td id=\"T_9d2d4_row14_col1\" class=\"data row14 col1\" >-3.66%</td>\n",
       "      <td id=\"T_9d2d4_row14_col2\" class=\"data row14 col2\" ></td>\n",
       "      <td id=\"T_9d2d4_row14_col3\" class=\"data row14 col3\" ></td>\n",
       "      <td id=\"T_9d2d4_row14_col4\" class=\"data row14 col4\" ></td>\n",
       "      <td id=\"T_9d2d4_row14_col5\" class=\"data row14 col5\" ></td>\n",
       "      <td id=\"T_9d2d4_row14_col6\" class=\"data row14 col6\" ></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x1761a72e0>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "B_W_Metric_raw = dataset[['difficulty', 'stability', 'p', 'y']].copy()\n",
    "B_W_Metric_raw['s_bin'] = B_W_Metric_raw['stability'].map(lambda x: round(math.pow(1.4, math.floor(math.log(x, 1.4))), 2))\n",
    "B_W_Metric_raw['d_bin'] = B_W_Metric_raw['difficulty'].map(lambda x: int(round(x)))\n",
    "B_W_Metric = B_W_Metric_raw.groupby(by=['s_bin', 'd_bin']).agg('mean').reset_index()\n",
    "B_W_Metric_count = B_W_Metric_raw.groupby(by=['s_bin', 'd_bin']).agg('count').reset_index()\n",
    "B_W_Metric['B-W'] = B_W_Metric['p'] - B_W_Metric['y']\n",
    "n = len(dataset)\n",
    "bins = len(B_W_Metric)\n",
    "B_W_Metric_pivot = B_W_Metric[B_W_Metric_count['p'] > max(50, n / (3 * bins))].pivot(index=\"s_bin\", columns='d_bin', values='B-W')\n",
    "B_W_Metric_pivot.apply(pd.to_numeric).style.background_gradient(cmap='seismic', axis=None, vmin=-0.2, vmax=0.2).format(\"{:.2%}\", na_rep='')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R_Metric:  0.03977842944422588\n",
      "R-squared: -6.8749\n",
      "RMSE: 0.1527\n",
      "[0.68927589 0.25115013]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Universal Metric of FSRS: 0.0123\n",
      "Universal Metric of SM2: 0.0833\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def sm2(history):\n",
    "    ivl = 0\n",
    "    ef = 2.5\n",
    "    reps = 0\n",
    "    for delta_t, rating in history:\n",
    "        delta_t = delta_t.item()\n",
    "        rating = rating.item() + 1\n",
    "        if rating > 2:\n",
    "            if reps == 0:\n",
    "                ivl = 1\n",
    "                reps = 1\n",
    "            elif reps == 1:\n",
    "                ivl = 6\n",
    "                reps = 2\n",
    "            else:\n",
    "                ivl = ivl * ef\n",
    "                reps += 1\n",
    "        else:\n",
    "            ivl = 1\n",
    "            reps = 0\n",
    "        ef = max(1.3, ef + (0.1 - (5 - rating) * (0.08 + (5 - rating) * 0.02)))\n",
    "        ivl = max(1, round(ivl+0.01))\n",
    "    return ivl\n",
    "\n",
    "dataset['sm2_interval'] = dataset['tensor'].map(sm2)\n",
    "dataset['sm2_p'] = np.exp(np.log(0.9) * dataset['delta_t'] / dataset['sm2_interval'])\n",
    "cross_comparison = dataset[['sm2_p', 'p', 'y']].copy()\n",
    "\n",
    "R_Metric = mean_squared_error(cross_comparison['y'], cross_comparison['sm2_p'], squared=False) - mean_squared_error(cross_comparison['y'], cross_comparison['p'], squared=False)\n",
    "print(\"R_Metric: \", R_Metric)\n",
    "plot_brier(dataset['sm2_p'], dataset['y'], bins=40)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(6, 6))\n",
    "\n",
    "cross_comparison['SM2_B-W'] = cross_comparison['sm2_p'] - cross_comparison['y']\n",
    "cross_comparison['SM2_bin'] = cross_comparison['sm2_p'].map(lambda x: round(x, 1))\n",
    "cross_comparison['FSRS_B-W'] = cross_comparison['p'] - cross_comparison['y']\n",
    "cross_comparison['FSRS_bin'] = cross_comparison['p'].map(lambda x: round(x, 1))\n",
    "\n",
    "plt.axhline(y = 0.0, color = 'black', linestyle = '-')\n",
    "\n",
    "cross_comparison_group = cross_comparison.groupby(by='SM2_bin').agg({'y': ['mean'], 'FSRS_B-W': ['mean'], 'p': ['mean', 'count']})\n",
    "print(f\"Universal Metric of FSRS: {mean_squared_error(cross_comparison_group['y', 'mean'], cross_comparison_group['p', 'mean'], sample_weight=cross_comparison_group['p', 'count'], squared=False):.4f}\")\n",
    "cross_comparison_group['p', 'percent'] = cross_comparison_group['p', 'count'] / cross_comparison_group['p', 'count'].sum()\n",
    "plt.scatter(cross_comparison_group.index, cross_comparison_group['FSRS_B-W', 'mean'], s=cross_comparison_group['p', 'percent'] * 1024, alpha=0.5)\n",
    "plt.plot(cross_comparison_group['FSRS_B-W', 'mean'], label='FSRS by SM2')\n",
    "\n",
    "cross_comparison_group = cross_comparison.groupby(by='FSRS_bin').agg({'y': ['mean'], 'SM2_B-W': ['mean'], 'sm2_p': ['mean', 'count']})\n",
    "print(f\"Universal Metric of SM2: {mean_squared_error(cross_comparison_group['y', 'mean'], cross_comparison_group['sm2_p', 'mean'], sample_weight=cross_comparison_group['sm2_p', 'count'], squared=False):.4f}\")\n",
    "cross_comparison_group['sm2_p', 'percent'] = cross_comparison_group['sm2_p', 'count'] / cross_comparison_group['sm2_p', 'count'].sum()\n",
    "plt.scatter(cross_comparison_group.index, cross_comparison_group['SM2_B-W', 'mean'], s=cross_comparison_group['sm2_p', 'percent'] * 1024, alpha=0.5)\n",
    "plt.plot(cross_comparison_group['SM2_B-W', 'mean'], label='SM2 by FSRS')\n",
    "\n",
    "plt.legend(loc='lower center')\n",
    "plt.grid(linestyle='--')\n",
    "plt.title(\"SM2 vs. FSRS\")\n",
    "plt.xlabel('Predicted R')\n",
    "plt.ylabel('B-W Metric')\n",
    "plt.xlim(0, 1)\n",
    "plt.xticks(np.arange(0, 1.1, 0.1))\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "fsrs4anki",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.16"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
